In recent years the number of mobile computing devices has increased dramatically, creating the need for more advanced mobile and wireless services. Mobile email, walkie-talkie services, multi-player gaming and call following are just a few examples of new applications that are emerging on mobile devices. In addition, mobile users are beginning to demand applications that not only utilize their current location but also share that location information with others. For example, parents wish to keep track of their children, supervisors need to track the location of their companies' delivery vehicles, and business travelers desire to search for nearby pharmacies to pick up prescriptions. All of these examples require the individual to know their own location or that of someone else.
To date, individuals have relied on asking for directions, calling someone to ask their whereabouts or having workers check-in from time to time with their positions. Location-based services are an emerging area of mobile applications that leverages the ability of new devices to calculate their current geographic position and report it to a mobile user or to a service. Some examples of these services include local weather, traffic updates, driving directions, child trackers, buddy finders and urban concierge services.
These new location sensitive devices rely on a variety of technologies that use the same general concept. Using radio signals coming from known reference points, these devices can mathematically calculate the mobile user's position relative to the reference points. Each of these approaches has its strengths and weaknesses based on the radio technology and the positioning algorithms they employ.
Retailers and advertisers are interested in consumer reaction to promotions and ads. More particularly, retailers and advertisers are interested in store/venue walk-ins as the key metric of success of their marketing efforts. Various venue walk-in detection methods have been utilized. These methods include, but are not limited to: (i) NFC-based check-in; (ii) barcode-based check-in; and (iii) location-based check-in. There are known limitations for (i) and (ii), such as the need for special software and hardware support on a user device and special hardware within the venue.
The location-based method is promising, provided that a high level of accuracy can be achieved even when small venues are geographically adjacent to each other. The barriers to achieve this to date include, but are not limited to: (i) the inability of GPS to provide acceptable coverage in indoor and densely populated areas due to satellite signal disruption, as well as its overall low accuracy (normally within the range of 10 meters); and (ii) the fact that 3G/4G-based networks are imprecise, and a location circle radius can be on the order of hundreds of meters or even a kilometer.
Wi-Fi has significant potential for location-based check-in. Efforts have been made in the industry to implement trilateration and radio frequency (RF) fingerprinting based methods. However, these methods have known limitations including, but not limited to: (i) in the case of trilateration, precise mathematics work well in open space or well-modeled environments where certain types and physical configurations of obstacles are presumed, but do not work well for generic cases such as a downtown city area with a multitude of stores, each with its own configuration of doors and walls; and (ii) RF fingerprinting requires special preparation such as scanning of the venue to build the reference fingerprint map, and periodic recalibration to accommodate changes in physical configuration and other radio emitters (e.g., other Wi-Fi access points, microwaves, and the like).
What is needed, then, are improved techniques that overcome the above limitations.